7th International Conference on Computational Social Science IC2S2

Abstract

Economic inequality is on the rise in Western societies and ‘meritocracy’ remains a widespread narrative used to justify it. An emerging literature has documented the impact of meritocratic narratives in media, mostly focusing on newspapers. In this paper, we study music as a potential source of cultural frames about economic inequality. We construct an original dataset combining user data from Spotify with lyrics from Genius to inductively explore whether popular music features themes of economic inequality. In order to do so, we employ unsupervised computational text analysis to classify the content of the 3,660 most popular songs across 23 European countries. Informed by Lizardo’s enculturation framework, we study popular music lyrics through the lens of public culture and explore its links with individual beliefs about inequality as a reflection of private culture. We find that, in more unequal societies, songs that frame inequalities as a structural issue (songs about “Struggle” or omnipresent “Risks”) are more popular than those adopting a meritocratic frame (songs we describe as “Bragging Rights” or those telling a “Rags to Riches” tale). Moreover, we find that the presence in public culture of a certain frame is associated with the expression of frame-consistent individual beliefs about inequality (private culture). We conclude by offering reflections on the promise of automatic text classification for the study of music lyrics, the theorized role of popular music in the study of culture, and by proposing venues for future research.

Date
Event
7th International Conference on Computational Social Science IC2S2
Location
ETH Zürich (virtual)
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Luca Carbone
Empirical Social Scientist